We introduce a Wasserstein distributionally robust Kalman filter that hedges against model risk. The filter can be computed efficiently by solving a sequence of ...
Sep 24, 2018 · We study a distributionally robust mean square error estimation problem over a nonconvex Wasserstein ambiguity set containing only normal distributions.
We study a distributionally robust mean square error estimation problem over a nonconvex Wasserstein ambiguity set containing only normal distributions. We show ...
We study a distributionally robust mean square error estimation problem over a nonconvex Wasserstein ambiguity set containing only normal distributions. We.
This paper proposes to use Wasserstein ambiguity sets to model uncertainty in the state estimation problem. The most relevant literature is H infinity ...
(PDF) Wasserstein Distributionally Robust Kalman Filtering
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Sep 8, 2024 · We study a distributionally robust mean square error estimation problem over a nonconvex Wasserstein ambiguity set containing only normal ...
Dec 3, 2018 · We study a distributionally robust mean square error estimation problem over a nonconvex Wasserstein ambiguity set containing only normal ...
We study a distributionally robust mean square error estimation problem over a nonconvex Wasserstein ambiguity set containing only normal distributions.
This paper presents a novel Wasserstein distributionally robust control and state estimation algorithm for partially observable linear stochastic systems.
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Wasserstein Distributionally. Robust Kalman Filtering. Soroosh Shafieezadeh ... Kalman filtering. Robustness reduces regret. Wasserstein filter displays ...